In July, we posted a blog post titled, “Humans Need Not Apply: What Happens When There’s No More Work?”As we mentioned in that post, the rise of artificial intelligence, machine learning, and robotics, have increasingly ominous implications for the future of work and employment. In a recent New York Times article, “The Long-Term Jobs Killer Is Not China. It’s Automation,” Claire Caine Miller traces the effects of automation on those who have been employed in America’s once preeminent industries—steel, coal, newspapers, etc. She observes that it is neither immigration nor globalization that threatens American workers; it’s automation. Referring to the recent 2016 political campaigns Caine Miller notes, “No candidate talked much about automation on the campaign trail. Technology is not as convenient a villain as China or Mexico, there is no clear way to stop it, and many of the technology companies are in the United States and benefit the country in many ways.” She quotes one study that shows that roughly 13 percent of manufacturing job losses are due to trade, and the rest are due to enhanced productivity attributable to automation.

In another article, “Evidence That Robots Are Winning the Race for American Jobs,”Caine Miller writes, “The industry most affected by automation is manufacturing. For every robot per thousand workers, up to six workers lost their jobs and wages fell by as much as three-fourths of a percent, according to a new paper by the economists, Daron Acemoglu of M.I.T. and Pascual Restrepo of Boston University.” In “How to Make America’s Robots Great Again” Farhad Manjoo, (New York Times, January 25, 2017) states, “Thanks to automation, we now make 85 percent more goods than we did in 1987, but with only two-thirds the number of workers.”

Manufacturing however, is not the only area where AI and robots threaten to displace human employees. In “A Robot May Be Training to Do Your Job. Don’t Panic,” Alexandra Levit argues that automation in the form of “social robotics,’ affective computing, and emotional awareness software, are now making inroads into the helping/caring professions, like nursing. Levit writes, “Eventually, the moment will come when machines possess empathy, the ability to innovate and other traits we perceive as uniquely human. What then? How will we sustain our own career relevance?”

According to these and other writers, automation and Artificial Intelligence are poised to sweep away or profoundly transform a number of occupations, and thereby alter both industry and society. While some writers foresee productive partnerships between AI and human colleagues, others warn that automation is likely to reduce the needs for human labor, and relegate sectors of the population to hard scrabble redundancy. As Martin Ford points out, this industrial revolution is different than previous ones, because new technology is taking aim at both blue and white collar work. (See Rise of the Robots: Technology and the Threat of a Jobless Future, by Martin Ford.)

Lest we become disconsolate at the prospect that robots will take our jobs, Claire Caine Miller suggests that there are a number of things that the US can do to prepare and adapt to these employment- threatening developments. She suggests that: 1) the US provide more and different kinds of education to employees, including teaching technical skills, like coding and statistics, and skills that still give humans an edge over machines, like creativity and collaboration; 2) creating better jobs for human workers including government subsidized employment (creating public sector jobs) and building infrastructure; 3) creating more care-giving jobs, strengthening labor unions, and training some workers to work in advanced manufacturing; 4)expanding the earned-income tax credit, providing a universal basic income, in which the government gives everyone a guaranteed amount of money, and establishing “ portable benefits” that wouldn’t be tied to a job to get health insurance. Caine Miller also suggests raising the minimum wage and even taxing robots (the latter, a proposal supported by Bill Gates.)

Whether these proposals will prove to be politically feasible or economically viable is difficult to judge. Some of these seem wildly utopian and difficult to envision—especially given a new Administration that built substantial electoral support on promises to revive employment in ‘smokestack’ industries, like steel and coal. That said, until relatively recently, it was difficult to envision the meteoric “rise of the robots” and the consequent effects on employment and society that such a development would have. Not even robots can reliably predict the future.